nameClusters: Clusters renaming

In RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

Clusters renaming

Description

Assign a class name to each cluster obtained by unsupervised or semi-supervised classification, thanks to the use of a training set and the majority rule method.

Usage

nameClusters(data.sample, method, RclusTool.env = initParameters())

Arguments

data.sample	list containing features, profiles and clustering results.
method	character vector specifying the clustering method (already performed) to use.
RclusTool.env	environment in which all global parameters, raw data and results are stored.

Details

nameClusters assigns a class name to each cluster obtained by unsupervised or semi-supervised classification, thanks to the use of a training set and the majority rule method

Value

data.sample list containing features, profiles and clustering results with updated labels names.

Examples

## Not run: 
dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))
tf1 <- tempfile()
write.table(dat, tf1, sep=",", dec=".")

x <- importSample(file.features=tf1)
x <- computeUnSupervised(x, K=3, method.name="K-means")

nameClusters(x, method = "K-means_preprocessed")



## End(Not run)

RclusTool documentation built on Aug. 29, 2022, 9:07 a.m.